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TingsongYu/PyTorch-Tutorial-2nd

A free, open-source Chinese-language book and companion code for learning PyTorch, from basics to CV, NLP, LLM applications and deployment.

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What is it?

This is the second edition of a Chinese-language PyTorch tutorial book, published as free online reading with companion code in the same repository. It is organized in three parts: fundamentals covering environment setup, data, models, optimization and visualization; applied projects in computer vision, natural language processing and large language models; and deployment with ONNX and TensorRT, including PTQ and QAT quantization.

The application section covers image classification, segmentation, object detection, object tracking, GAN and diffusion generation, image captioning and image retrieval. The NLP part covers RNN, LSTM, Transformer, BERT and GPT models with tasks such as text classification, machine translation, named entity recognition and QA. The LLM section walks through deploying Qwen, ChatGLM, Baichuan and Yi, plus a GPT Academic project.

The book is licensed for non-commercial use under CC BY-NC 4.0, and the content is written in Simplified Chinese.

Key features

  • 01Covers PyTorch fundamentals including data, models, optimization and visualization
  • 02Includes computer vision projects such as detection, segmentation and tracking
  • 03Covers NLP models from RNN to GPT with practical tasks
  • 04Demonstrates deploying open-source LLMs such as Qwen, ChatGLM, Baichuan and Yi
  • 05Explains model export with ONNX and TensorRT, plus PTQ and QAT quantization

Use cases

  • Learning PyTorch from scratch with a structured Chinese-language course
  • Finding worked examples for CV or NLP projects to adapt
  • Following a path from model training to ONNX or TensorRT deployment
  • Getting hands-on with running open-source LLMs locally

Quick start

  1. 1

    Read the book online for free

  2. 2

    Open the companion code repository on GitHub

Things to know

  • Licensed under CC BY-NC 4.0, so commercial use is not permitted.
  • The book and its examples are written in Chinese.

Topics

#pytorch#deep-learning#tutorial#computer-vision#nlp#llm#onnx#tensorrt#deepsort#diffusion-models

FAQ

What is PyTorch-Tutorial-2nd?
A free, open-source Chinese-language book and companion code for learning PyTorch, from basics to CV, NLP, LLM applications and deployment. This is the second edition of a Chinese-language PyTorch tutorial book, published as free online reading with companion code in the same repository. It is organized in three parts: fundamentals covering environment setup, data, models, optimization and visualization; applied projects in computer vision, natural language processing and large language models; and deployment with ONNX and TensorRT, including PTQ and QAT quantization.
Is PyTorch-Tutorial-2nd free to use? What license does it have?
PyTorch-Tutorial-2nd has no declared license. Its code is public, but without a license you have no explicit permission to reuse it; ask the author before relying on it.
Is PyTorch-Tutorial-2nd still maintained?
Actively maintained. The last commit to PyTorch-Tutorial-2nd was on Oct 15, 2026.
What can I use PyTorch-Tutorial-2nd for?
Learning PyTorch from scratch with a structured Chinese-language course Finding worked examples for CV or NLP projects to adapt Following a path from model training to ONNX or TensorRT deployment Getting hands-on with running open-source LLMs locally
How do I install PyTorch-Tutorial-2nd?
Read the book online for free Open the companion code repository on GitHub
Where can I get PyTorch-Tutorial-2nd?
The source code and installation instructions are on GitHub: https://github.com/TingsongYu/PyTorch-Tutorial-2nd

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